Abstract
In recent years, many industrialfacilities have been required to install sensing system to monitor the health status of the equipment. Although the PC-based diagnosis system is a good alternative, it undoubtedly increases the hardware cost greatly, and also causes restrictions on system assembly. In some critical environments, installation of the PC-based system is not suitable because of high temperature, dust, and humidity. On the contrary, a high mobility portable smart sensor will be relatively adequate for onsite inspections. To solve this problem, we developed a low-cost embedded handheld smart sensor. Instead of using sophisticated algorithms, certain frequently used statistic indicators are considered. Nevertheless, due to the resource limitations of the embedded systems, it causes difficulty for real-time realization and therefore, the recursive architecture of the statistic indicators is derived. These statistical factors are then fed into a Gaussian classifier for online defect detection, which gives a great contribution to field operators for onsite inspections. The highly integrated hardware/software co-design of the developed device provides user-friendly and high mobility for field inspections. Finally, a practical industrial application regarding the online diagnosis of a solenoid valve actuator defect is presented to demonstrate the effectiveness of the developed embedded smart sensor.
Highlights
Embedded systems have been widely integrated in smart intelligent sensing system applications [1] owing to its high security [2], compact size [3], efficient power consumption [4], high stability and affordable cost
Most of the vibration-based fault detection methods use the accelerometers as their main sensing sources
Owing to its cost and size advantages, in many semiconductor industries, the micro-electro-mechanical-systems (MEMS) type accelerometer [7] is already taken as the chief sensor for machine actuator defect online detection
Summary
Embedded systems have been widely integrated in smart intelligent sensing system applications [1] owing to its high security [2], compact size [3], efficient power consumption [4], high stability and affordable cost. The main contribution of this paper include: derivations of the statistic measurement indices in the recursive forms; computational efficient embedded architecture for algorithm realization; applying Gaussian classifier for detect detection; hardware/software co-design of a low-cost handheld smart vibration analyzer, and a practical case study is presented to validate the feasibility of the developed smart sensor. Put it the developed smart handheld vibration analyzer can be used to detect whether an actuator, e.g. a solenoid valve, is going to be defective
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